1. Field of the Invention
This invention relates to techniques for recovering an original image from its halftone version. The techniques may be implemented in an apparatus, as methods, or as programs of instructions for directing an apparatus or machine to carry out the processing steps of these techniques.
2. Description of the Related Art
Continuous tone images are converted to halftone images for printing. Halftones are binary or multi-level images, and bi- or multi-level dithering used to generate them creates the effect of continuous tones by trading off color depth against spatial resolution. While halftones are excellent for printing, they do not lend themselves well to certain processing, such as scaling or enhancement. Halftones are also not very compressible. Thus, a halftone is normally reconverted to a continuous tone image to enable such processing and then converted back to a halftone before printing.
One known and relatively simple way to reconstruct an original image from its halftone version involves applying a smoothing low-pass filter (LPF) to the halftone version. At each pixel location, the output value of the LPF is kept if the absolute color distance between the halftone value and the LPF output value is less than a predetermined distance; otherwise, the halftone value is used. Mathematically, this simple reconstruction proceeds as follows:
                                                           y              _                        =                        ⁢                          H              *              y                                ,                                    where              ⁢                                                          ⁢              H                        =                          smoothing              ⁢                                                          ⁢              LPF                                                                              ⁢                                                    y                _                            ⁢                                                          ⁢              if              ⁢                                                          ⁢                                                                y                  -                                      y                    _                                                                                        <            Δ                                                                                  y              ^                        =                    ⁢                                                                                                                                                                                     ⁢                        ⁢            y            ⁢                                                  ⁢            if            ⁢                                                  ⁢                                                        y                -                                  y                  _                                                                            >          Δ                                                          where            ⁢                                                                      ⁢                                                                    ⁢            Δ                    =                    ⁢                      difference            ⁢                                                  ⁢            between            ⁢                                                  ⁢            adjacent            ⁢                                                  ⁢            dither            ⁢                                                  ⁢            levels                              
The problem with this approach is that it tends to introduce blurring into the reconstructed image.